• Journal of Integrative Natural Science
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• v.7 no.1
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• pp.62-66
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• 2014

This study aims to implement the emergency monitoring robot system which predicts the current state of the patients without visiting the medical institutions by measuring the basic health status of the user's blood pressure, heartbeat, and basic health status of body temperature in the disaster emergency situation based on the Smart Grid. By arranging a large number of sensor(blood pressure, heartbeat, body temperature sensor) and measuring the bio signs, so the attached wireless XBee sensor can be stored in DB of robot, and it aims to draw the current state of the patients by analysis of stored bio data. Among 300 data obtained from the sensor, 1st data to 100th data were used for learning, and from 101st data to 300th data were used for assessment. 12 results were different among the total 300 assessment data, so it shows about 96% accuracy.

• Smart Structures and Systems
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• v.6 no.1
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• pp.87-90
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• 2010

• Magazine of the Korea Concrete Institute
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• v.24 no.3
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• pp.34-36
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• 2012

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.429-432
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• 2007

For smart structure technologies, the interests in wireless sensor networks for structural health monitoring are growing. The wireless sensor networks reduce the installation of the wire embedded in the whole structure and save the costs. But the wireless sensor networks have lots of limits and there are lots of researches and developments of wireless sensor and the network for data process. Most of the researches of wireless sensor network is applying to the civil engineering structure and the researches for the highrise building are required. And strain-based SHM gives the local damage information of the structures which acceleration-based SHM can not. In this paper, concept of wireless sensor network for structural health monitoring of highrise building is suggested. And verifying the feasibility of the strain-based SHM a strain sensor board has developed and tested by experiments.

• Smart Structures and Systems
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• v.5 no.4
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• pp.397-413
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• 2009

Composite bridges offer many advantages compared to current steel and aluminum bridges. This paper presents the results of a comprehensive on-going research program to develop innovative Diagnostic Prognostic System (DPS) and a structural evaluation of Composite Army Bridge (CAB) system. The DPS is founded on three technologies: optical fiber sensing, remote data transmission, and virtual testing. In developing this system, both laboratory and virtual test were used in different damage scenarios. Health monitoring with DPS entailed comparing live strain data to archived strained data in various bridge locations. For field repairs, a family of composite chords was subjected to simple ramp loads in search of ultimate strength. As such, composite bridge specimens showcased their strengths, heralded the viability of virtual testing, highlighted the efficacy of field repair, and confirmed the merits of health monitoring.

• Smart Structures and Systems
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• v.5 no.4
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• pp.369-379
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• 2009

The sudden collapse of Interstate 35 Bridge in Minneapolis gave a wake-up call to US municipalities to re-evaluate aging bridges. In this situation, structural health monitoring (SHM) technology can provide the essential help needed for monitoring and maintaining the nation's infrastructure. Monitoring long span bridges such as cable-stayed bridges effectively requires the use of a large number of sensors. In this article, we introduce a probabilistic approach to identify optimal locations of sensors to enhance damage detection. Probability distribution functions are established using an artificial neural network trained using a priori knowledge of damage locations. The optimal number of sensors is identified using multi-objective optimization that simultaneously considers information entropy and sensor cost-objective functions. Luling Bridge, a cable-stayed bridge over the Mississippi River, is selected as a case study to demonstrate the efficiency of the proposed approach.

• Smart Structures and Systems
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• v.11 no.3
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• pp.261-282
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• 2013

Structural health monitoring (SHM) is an application area of Wireless Sensor Networks (WSNs) which usually needs high data communication rate to transfer a large amount of monitoring data. Traditional sink node can only process data from one communication channel at the same time because of the single radio chip structure. The sink node constitutes a bottleneck for constructing a high data rate SHM application giving rise to a long data transfer time. Multi-channel communication has been proved to be an efficient method to improve the data throughput by enabling parallel transmissions among different frequency channels. This paper proposes an 8-radio integrated sink node design method based on Field Programmable Gate Array (FPGA) and the time synchronization mechanism for the multi-channel network based on the proposed sink node. Three experiments have been performed to evaluate the data transfer ability of the developed multi-radio sink node and the performance of the time synchronization mechanism. A high data throughput of 1020Kbps of the developed sink node has been proved by experiments using IEEE.805.15.4.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1019-1039
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• 2015

Shanghai Tower is a composite structure building with a height of 632 m. In order to verify the structural properties and behaviors in construction and operation, a structural health monitoring project was conducted by Tongji University. The monitoring system includes sensor system, data acquisition system and a monitoring software system. Focusing on the health monitoring in construction, this paper introduced the monitoring parameters in construction, the data acquisition strategy and an integration structural health monitoring (SHM) software. The integration software - Structural Monitoring/ Analysis/ Evaluation System (SMAE) is designed based on integration and modular design idea, which includes on-line data acquisition, finite elements and dynamic property analysis functions. With the integration and modular design idea, this SHM system can realize the data exchange and results comparison from on-site monitoring and FEM effectively. The analysis of the monitoring data collected during the process of construction shows that the system works stably, realize data acquirement and analysis effectively, and also provides measured basis for understanding the structural state of the construction. Meanwhile, references are provided for the future automates construction monitoring and implementation of high-rise building structures.

• Smart Structures and Systems
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• v.7 no.4
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• pp.303-317
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• 2011

A specially designed tendon, which is proposed by embedding an FBG sensor into the center king cable of a 7-wire strand tendon, was applied to monitor the prestress force and load transfer of ground anchor. A series of tensile tests and a model pullout test were performed to verify the feasibility of the proposed smart tendon as a measuring sensor of tension force and load transfer along the tendon. The smart tendon has proven to be very effective for monitoring prestress force and load transfer by measuring the strain change of the tendon at the free part and the fixed part of ground anchor, respectively. Two 11.5 m long proto-type ground anchors were made simply by replacing a tendon with the proposed smart tendon and prestress forces of each anchor were monitored during the loading-unloading step using both FBG sensor embedded in the smart tendon and the conventional load cell. By comparing the prestress forces measured by the smart tendon and load cell, it was found that the prestress force monitored from the FBG sensor located at the free part is comparable to that measured from the conventional load cell. Furthermore, the load transfer of prestressing force at the tendon-grout interface was clearly measured from the FBGs distributed along the fixed part. From these pullout tests, the proposed smart tendon is not only expected to be an alternative monitoring tool for measuring prestress force from the introducing stage to the long-term period for health monitoring of the ground anchor but also can be used to improve design practice through determining the economic fixed length by practically measuring the load transfer depth.

• Smart Structures and Systems
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• v.15 no.1
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• pp.151-167
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• 2015

Instrumentation on structural health monitoring system imposes critical issues for applying the structural monitoring system to real world structures, for which not only on the configuration and geometry, but also aesthetics on the system to be monitored should be considered. To illustrate this point, two real world structural health monitoring systems, the structural health monitoring system of Shenzhen Vanke Center and the structural health monitoring system of Shenzhen Bay Stadium in China, are presented in the paper. The instrumentation on structural health monitoring systems of real world structures is addressed by providing the description of the structure, the purpose of the structural health monitoring system implementation, as well as details of the system integration including the installations on the sensors and acquisition equipment and so on. In addition, an intelligent algorithm on stress identification using measurements from multi-region is presented in the paper. The stress identification method is deployed using the fuzzy pattern recognition and Dempster-Shafer evidence theory, where the measurements of limited strain sensors arranged on structure are the input data of the method. As results, at the critical parts of the structure, the stress distribution evaluated from the measurements has shown close correlation to the numerical simulation results on the steel roof of the Beijing National Aquatics Center in China. The research work in this paper can provide a reference for the design and implementation of both real world structural health monitoring systems and intelligent algorithm to identify stress distribution effectively.